Identification of a New Candidate Locus for Ebstein Anomaly in 1p36.2

Dimensionality reduction approach for many-objective epistasis analysis

In epistasis analysis, single-nucleotide polymorphism-single-nucleotide polymorphism interactions (SSIs) among genes may, alongside other environmental factors, influence the risk of multifactorial diseases. To identify SSI between cases and controls (i.e. binary traits), the score for model quality is affected by different objective functions (i.e. measurements) because of potential disease model preferences and disease complexities. Our previous study proposed a multiobjective approach-based multifactor dimensionality reduction (MOMDR), with the results indicating that two objective functions could enhance SSI identification with weak marginal effects. However, SSI identification using MOMDR remains a challenge because the optimal measure combination of objective functions has yet to be investigated. This study extended MOMDR to the many-objective version (i.e. many-objective MDR, MaODR) by integrating various disease probability measures based on a two-way contingency table to improve the identification of SSI between cases and controls. We introduced an objective function selection approach to determine the optimal measure combination in MaODR among 10 well-known measures. In total, 6 disease models with and 40 disease models without marginal effects were used to evaluate the general algorithms, namely those based on multifactor dimensionality reduction, MOMDR and MaODR. Our results revealed that the MaODR-based three objective function model, correct classification rate, likelihood ratio and normalized mutual information (MaODR-CLN) exhibited the higher 6.47% detection success rates (Accuracy) than MOMDR and higher 17.23% detection success rates than MDR through the application of an objective function selection approach. In a Wellcome Trust Case Control Consortium, MaODR-CLN successfully identified the significant SSIs (P < 0.001) associated with coronary artery disease. We performed a systematic analysis to identify the optimal measure combination in MaODR among 10 objective functions. Our combination detected SSIs-based binary traits with weak marginal effects and thus reduced spurious variables in the score model. MOAI is freely available at https://sites.google.com/view/maodr/home.

Genetic Analysis Algorithm for the Study of Patients with Multiple Congenital Anomalies and Isolated Congenital Heart Disease

Congenital anomalies (CA) affect 3–5% of newborns, representing the second-leading cause of infant mortality in Argentina. Multiple congenital anomalies (MCA) have a prevalence of 2.26/1000 births in newborns, while congenital heart diseases (CHD) are the most frequent CA with a prevalence of 4.06/1000 births. The aim of this study was to identify the genetic causes in Argentinian patients with MCA and isolated CHD. We recruited 366 patients (172 with MCA and 194 with isolated CHD) born between June 2015 and August 2019 at public hospitals. DNA from peripheral blood was obtained from all patients, while karyotyping was performed in patients with MCA. Samples from patients presenting conotruncal CHD or DiGeorge phenotype (n = 137) were studied using MLPA. Ninety-three samples were studied by array-CGH and 18 by targeted or exome next-generation sequencing (NGS). A total of 240 patients were successfully studied using at least one technique. Cytogenetic abnormalities were observed in 13 patients, while 18 had clinically relevant imbalances detected by array-CGH. After MLPA, 26 patients presented 22q11 deletions or duplications and one presented a TBX1 gene deletion. Following NGS analysis, 12 patients presented pathogenic or likely pathogenic genetic variants, five of them, found in KAT6B, SHH, MYH11, MYH7 and EP300 genes, are novel. Using an algorithm that combines molecular techniques with clinical and genetic assessment, we determined the genetic contribution in 27.5% of the analyzed patients.

Mitral Valve Prolapse and Its Motley Crew-Syndromic Prevalence, Pathophysiology, and Progression of a Common Heart Condition

Mitral valve prolapse (MVP) is a commonly occurring heart condition defined by enlargement and superior displacement of the mitral valve leaflet(s) during systole. Although commonly seen as a standalone disorder, MVP has also been described in case reports and small studies of patients with various genetic syndromes. In this review, we analyzed the prevalence of MVP within syndromes where an association to MVP has previously been reported. We further discussed the shared biological pathways that cause MVP in these syndromes, as well as how MVP in turn causes a diverse array of cardiac and noncardiac complications. We found 105 studies that identified patients with mitral valve anomalies within 18 different genetic, developmental, and connective tissue diseases. We show that some disorders previously believed to have an increased prevalence of MVP, including osteogenesis imperfecta, fragile X syndrome, Down syndrome, and Pseudoxanthoma elasticum, have few to no studies that use up-to-date diagnostic criteria for the disease and therefore may be overestimating the prevalence of MVP within the syndrome. Additionally, we highlight that in contrast to early studies describing MVP as a benign entity, the clinical course experienced by patients can be heterogeneous and may cause significant cardiovascular morbidity and mortality. Currently only surgical correction of MVP is curative, but it is reserved for severe cases in which irreversible complications of MVP may already be established; therefore, a review of clinical guidelines to allow for earlier surgical intervention may be warranted to lower cardiovascular risk in patients with MVP.

Integrated microRNA and mRNA Expression Profiling Identifies Novel Targets and Networks Associated with Ebstein's Anomaly

Little is known about abundance level changes of circulating microRNAs (miRNAs) and messenger RNAs (mRNA) in patients with Ebstein’s anomaly (EA). Here, we performed an integrated analysis to identify the differentially abundant miRNAs and mRNA targets and to identify the potential therapeutic targets that might be involved in the mechanisms underlying EA. A large panel of human miRNA and mRNA microarrays were conducted to determine the genome-wide expression profiles in the blood of 16 EA patients and 16 age and gender-matched healthy control volunteers (HVs). Differential abundance level of single miRNA and mRNA was validated by Real-Time quantitative PCR (RT-qPCR). Enrichment analyses of altered miRNA and mRNA abundance levels were identified using bioinformatics tools. Altered miRNA and mRNA abundance levels were observed between EA patients and HVs. Among the deregulated miRNAs and mRNAs, 76 miRNAs (49 lower abundance and 27 higher abundance, fold-change of ≥2) and 29 mRNAs (25 higher abundance and 4 lower abundance, fold-change of ≥1.5) were identified in EA patients compared to HVs. Bioinformatics analysis identified 37 pairs of putative miRNA-mRNA interactions. The majority of the correlations were detected between the lower abundance level of miRNA and higher abundance level of mRNA, except for let-7b-5p, which showed a higher abundance level and their target gene, SCRN3, showed a lower abundance level. Pathway enrichment analysis of the deregulated mRNAs identified 35 significant pathways that are mostly involved in signal transduction and cellular interaction pathways. Our findings provide new insights into a potential molecular biomarker(s) for the EA that may guide the development of novel targeting therapies.

Prenatal detection of 1p36 deletion syndrome: ultrasound findings and microarray testing results

OBJECTIVE

Only a small number of reports have been made on the prenatal ultrasound findings observed in 1p36 deletion syndrome. We explored prenatal diagnosis of 1p36 deletion by ultrasound as well as chromosomal microarray (CMA), and delineated the fetal presentation of this syndrome.

STUDY DESIGN

This was a retrospective analysis of 10 new prenatal cases of 1p36 deletion identified by CMA at a single Chinese medical center. Clinical data were reviewed for these cases, including maternal demographics, indications for invasive testing, sonographic findings, CMA results and pregnancy outcomes.

RESULTS

One case was diagnosed because of a positive cell-free DNA (cfDNA) testing result for terminal 1p deletion, and the remaining nine cases were identified because of an abnormal ultrasound findings, including early miscarriage, structural abnormalities and fetal growth restriction. CMA revealed 1p36 deletions to be terminal in six cases, and interstitial in four cases. Deletion sizes ranged from 1.7 to 42.7 Mb.

CONCLUSIONS

Prenatal findings such as cardiac malformations, especially Ebstein anomaly, and fetal growth retardation should warrant the diagnosis of 1p36 deletion and invasive genetic testing using CMA.